Do you struggle with your duties as a project manager?
It can get tough!
Considering endless variables for a schedule that just won’t come off as you’d like. Working to beat deadlines that appear a herculean task. Veering disastrously off track when you thought the project was perfectly on course.
And that’s not the end of it!
Repetitive chores await at the end of each cycle, making you want to pull your hair out. You’re also shackled by a budget, where tight is the understatement of the year.
Now and again, you think to yourself, is there a better way to do things?
The job of a project manager is the furthest thing from a walk in a park. But, with the right tools, it gets much easier. One option is to consider artificial intelligence applications in project management strategies.
Without further ado, let’s get into how AI can lend a helping hand so you keep your sanity:
1. Risk Assessment
What systems do you use to gauge a project’s probability of success and for keeping track?
You may have a cumbersome formula or excel spreadsheet you rely on for that. Yet, sometimes the numbers seem to lie.
Worse still, if you work out the odds by manually tracking past data, hand calculations, and strenuous in-person market research, you probably don’t roll out the welcome mat for every new project.
Each time you have to go through heaps of reports, figure out what worked, what failed, and why. Which, as you know, is way easier said than done.
Researching a new project is chaotic!
The groundwork alone takes days, sometimes even weeks, to conduct satisfactorily, and that doesn’t even guarantee the success of the project.
All that work could have been for nothing, not forgetting the resources spent along the way.
Artificial Intelligence in project management through predictive analytics can save you the time and costs of looking through past projects. These can predict a project’s future, and keep an eye on the deadline and budget to foresee risks so you can take corrective measures in time.
Companies such as Nike and Google have been using predictive analytics tools like ClickUp to get around planning headaches.
2. Resource Scheduling
For a project manager, getting your staff or resource selections wrong means that your project is doomed to fail from the start. You’ll either not meet deadlines or expensively go beyond the scope to get more hands on deck.
Problem is, you’d don’t always know everything you need at the start. Be it the best team member for a job, or all the additional skill sets that come in handy later on.
Project requirements sneak up on you like a heart attack!
AI-powered software can handle duty designation. It can:
- Work out available personnel
- Assign work to the most competent person
- Determine who’ll be occupied and for how long
- Calculate work quotients for everyone
The AI system chooses team members by drawing from a database that compiles each employee’s skills.
Also, the software can estimate how much work each person can handle through past productivity data. Hence, the project becomes time-efficient by reducing the backlog.
French multinational Cap Gemini has been handing resource scheduling duties to AI to streamline task allocation.
The company relies on IMB Watson for resource planning. Watson is a cognitive computing system with amazing data interpretation abilities.
3. Problem Solving
Every project is bound to run into a problem at one point or another. No matter how thorough or astute the planning is, something seems to always find a way to go wrong.
A project problem can crop up at the most inopportune time!
Instead of taking to the office to address out-of-the-blues difficulties at odd hours, a KBE system can sort out complications.
A knowledge-based expert system is designed to offer the expertise of a qualified professional. It contains operational information, and automatically fixes arising issues, or offers a recommendation. It is an incredible stand-in for human personnel. A KBE system has problem-solving and reasoning skills much like a human, usually adopted from past data of solved problems.
The KBES works off facts and knowledge input by the operator. It is founded upon conditional programming rules, mostly the “If-Then” clauses.
Artificial intelligence guides the software to first diagnose the state of the project. If certain pre-determined conditions are not met, the KBES moves into the problem phase. Here, it identifies the problem by its symptoms and offers a specific remedy.
Let’s explain with a simple example.
Suppose worker A doesn’t fulfill an assigned task within a certain period, the KEBS reshuffles it to worker B to keep the project on track.
For more complex problems, the system picks up the issue and quickly brings it to the attention of a human responder to ensure the complication is dealt with as soon as possible.
4. Automating Tasks
Recurring tasks are not only frustrating, but they also take up time that may have been better spent elsewhere. A good example of that would be the employee onboarding process in most companies. Each time a company gets a new hire, they go through the same onboarding process.
Similarly, every time you start a new project, a couple of tasks keep coming back.
Recurring work may be in the way of blending data from several sources, data entry, and similar data manipulation patterns.
A recent survey estimates that businesses lose about 19 working days every year to repetitive work.
The AI automation of recurring work can free up time for higher-value tasks.
Instead of sending emails or notice of project delays yourself, an AI system can do that for you. It can serve notices for missed payments and other chores that tend to keep on repeating.
But there’s more!
AI systems can also avoid the duplication of tasks among team members, which often leads to a lot of time wasted. With repetitive and duplicate tasks out of the way, you can trim the size of your team or shift resources somewhere more critical.
Construction company Bechtel Corporation, for instance, has RPA (robot process automation) systems that scan and processes invoices, harnessing the benefits of AI in project management.
5. Fraud Prevention
Fraud and budget misappropriations are something you deeply worry about as a project manager. It is one of the BIGGEST problems and can derail and even collapse a project in its entirety. The situation is especially challenging in a large company setting, where a single project can have dozens of team members.
How do you keep tabs on every worker and their pricing claims?
It’s almost impossible by human means alone to verify receipts, the number of items purchased, and even determine that the most competitive supplier was chosen.
AI software can detect payment anomalies and other red flags that indicate a project deviation according to set metrics of preliminary data. For example, if a team member buys a product that usually costs $20 for $30, that is pointed out and you can follow up on it and get to the bottom of the matter. A variation of the KBES can offer watchdog duties across various levels.
Small yet important details that would have slipped by you are highlighted.
Mastercard is already on the AI-fraud detection bandwagon. The financial services corporation is one of over 30 companies using AI-powered fraud detection software like Fraud.net, among others.
Conclusion
Do you believe artificial intelligence can help you be a better project manager?
Project management entails juggling a lot of things at the same time. Human beings are prone to mistakes especially when plagued with tedious, repetitive tasks that sap the life out of you. Moreover, devious team members can also pull a fast one on you. This can happen multiple times with you being none the wiser.
Artificial intelligence offers CRUCIAL benefits to any project management system, and AI practitioners predict its use will only increase in 2021.
AI-powered PM tools can assist you with automating repetitive tasks, anti-fraud measures, and scheduling resources for optimum operation.
You’ll certainly be a better manager with AI software on your side. Embrace artificial intelligence in your project management strategies.
